Wolfe线搜索下的修正FR谱共轭梯度法

doi:10.6040/j.issn.1671-9352.0.2016.406

山东大学学报（理学版） ›› 2017, Vol. 52 ›› Issue (4): 6-12.doi: 10.6040/j.issn.1671-9352.0.2016.406

Wolfe线搜索下的修正FR谱共轭梯度法

林穗华

广西民族师范学院数学与计算机科学系, 广西崇左 532200

收稿日期:2016-09-02 出版日期:2017-04-20 发布日期:2017-04-11
作者简介:林穗华(1973— ),女,硕士,副教授,研究方向为最优化方法及应用. E-mail:linsuihuah@163.com
基金资助:
广西高校科研重点项目(ZD2014143);广西重点培育学科(应用数学)建设项目(桂教科研［2013］16);广西民族师范学院科研项目(2013RCGG002)

A modified FR spectral conjugate gradient method with Wolfe line search

LIN Sui-hua

Department of Mathematics and Computer Science, Guangxi Normal University for Nationalities, Chongzuo 532200, Guangxi, China

Received:2016-09-02 Online:2017-04-20 Published:2017-04-11

摘要/Abstract

摘要： 对无约束优化问题的谱共轭共轭梯度法,提出修正的FR共轭参数和谱参数,使每次迭代均自行产生下降方向,且这一下降性不依赖于任何线搜索条件。在常规假设下,证明了采用Wolfe线搜索的新算法具有全局收敛性。相关的数值实验结果表明该谱共轭梯度法是有效的。

关键词: 无约束优化, Wolfe线搜索, 谱共轭梯度法, 全局收敛

Abstract: A modified FR spectral conjugate gradient method is proposed for unconstrained optimization. This method can automatically generate descent direction at every iterations depending on no any line search. Under the conventional assumption, it is proved that the corresponding method with Wolfe line search is globally convergent. The numerical results show that the spectral conjugate gradient method is effective.

Key words: spectral conjugate gradient method, Wolfe line search, global convergence, unconstrained optimization

中图分类号:

O221

林穗华. Wolfe线搜索下的修正FR谱共轭梯度法[J]. 山东大学学报（理学版）, 2017, 52(4): 6-12.

LIN Sui-hua. A modified FR spectral conjugate gradient method with Wolfe line search[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(4): 6-12.

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Wolfe线搜索下的修正FR谱共轭梯度法

A modified FR spectral conjugate gradient method with Wolfe line search

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